code: def test_no_batch_idx_gradient_accumulation():
      """Regression test for an issue where excluding the batch_idx from training_step would disable gradient
      accumulation."""
  
      class MyModel(BoringModel):
          last_batch_idx = -1
  
          def training_step(self, batch):  # no batch_idx
              return self.step(batch)
  
          def optimizer_step(self, epoch, batch_idx, *args, **kwargs):
              assert batch_idx in (1, 3)
              self.last_batch_idx = batch_idx
              return super().optimizer_step(
                  epoch, batch_idx, *args, **kwargs
              )
  
      trainer = Trainer(
          fast_dev_run=4, accumulate_grad_batches=2, limit_val_batches=0
      )
      model = MyModel()
      trainer.fit(model)
      assert model.last_batch_idx == 3
  
file_path: pytorch-lightning/tests/tests_pytorch/loops/test_training_epoch_loop.py
imports: import logging
  from unittest.mock import Mock, patch
  import pytest
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.trainer.trainer import Trainer
label_desc: Use image node_id 5 for calling a global function with example usage: test_no_batch_idx_gradient_accumulation() and returns: self, super